Spurious correlation #5,486 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Bozeman, Montana and the second variable is The number of blender tenders in Montana. The chart goes from 2003 to 2019, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Bozeman, Montana and the second variable is The number of blender tenders in Montana. The chart goes from 2003 to 2019, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution increased in Bozeman, it created a unique demand for individuals with the special skill set of "blender tending." These expert blenders were sought after to purify the air and ensure that everyone could still breathe easy. It's as if the job market was really just blending perfectly with the pollution levels!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image showing two contrasting scenes: In Bozeman, Montana, amidst air pollution, a group of individuals use giant blenders to purify the air. On one side, show the polluted sky and tangled fumes, and on the other, depict the clean, fresh air blending with the pollution. Represent this visual through a balanced ecosystem, symbolizing the harmonious coexistence of nature and human activity within an urban environment. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Air pollution in Bozeman, Montana and The number of blender tenders in Montana. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Glitch art Pop art Symbolism Hyper-realistic Sci-fi fantacy
ChatGPT: Symbolism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Bozeman, Montana and The number of blender tenders in Montana, in the following situation: As air pollution increased in Bozeman, it created a unique demand for individuals with the special skill set of "blender tending." These expert blenders were sought after to purify the air and ensure that everyone could still breathe easy. It's as if the job market was really just blending perfectly with the pollution levels!. Keep the description simple.
ChatGPT: In Bozeman, Montana, as air pollution increased, the demand for individuals skilled in "blender tending" became apparent. The town witnessed people using their expertise to purify the air, creating a visual of clean, fresh air blending with the pollution, symbolizing a balanced ecosystem in the midst of an urban environment.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Symbolism ] and depicting this scene: In Bozeman, Montana, as air pollution increased, the demand for individuals skilled in "blender tending" became apparent. The town witnessed people using their expertise to purify the air, creating a visual of clean, fresh air blending with the pollution, symbolizing a balanced ecosystem in the midst of an urban environment. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image showing two contrasting scenes: In Bozeman, Montana, amidst air pollution, a group of individuals use giant blenders to purify the air. On one side, show the polluted sky and tangled fumes, and on the other, depict the clean, fresh air blending with the pollution. Represent this visual through a balanced ecosystem, symbolizing the harmonious coexistence of nature and human activity within an urban environment.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Air pollution in Bozeman, Montana positively influenced The number of blender tenders in Montana. Include one good pun.

AI academic paper

(Because p < 0.01)

Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana

Journal of Ecological Appliance Studies

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Bozeman, Montana and The number of blender tenders in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
"Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.

With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.

In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between environmental factors and labor market trends is often an unexplored territory, akin to traversing through a dense, smog-filled forest with nothing but a blender in hand. However, in the spirit of blending seemingly unrelated ideas, this study delves into the rather unconventional link between air pollution levels in Bozeman, Montana, and the workforce of blender tenders in the state.
Air pollution, a noxious blend of gases and particles, has long been a cause for concern due to its adverse effects on human health and the environment. Yet, who would have thought that amidst this chemical cocktail of pollutants, there lies a hitherto uncharted correlation with the number of individuals tending to the humble blender, the unsung hero of many a kitchen concoction?
Uncovering such unexpected connections between seemingly unrelated variables can be likened to accidentally mixing vinegar with milk – surprising, puzzling, and often leading to unexpected outcomes. Nevertheless, it is within these unexpected outcomes that the potential for groundbreaking discoveries often lies, much like finding a hidden gem in a box of kitchen gadgets.
Integrating data from the Environmental Protection Agency and the Bureau of Labor Statistics, our study aims to unravel the tangled blend of factors influencing the demand for blender tenders in Montana. The analysis uncovers a strong correlation between air pollution levels in Bozeman and the number of blender tenders in the state, akin to finding the perfect blend of ingredients for an elusive recipe.
The unexpected nature of the findings serves as a stark reminder of the complexity of real-world phenomena, akin to discovering a hidden blender feature after years of use – it may be surprising, but it sheds new light on an everyday appliance. As we navigate through the web of air pollution and labor market dynamics, it becomes evident that this seemingly inconspicuous correlation has broader implications for understanding regional economic dynamics amidst environmental challenges.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The authors find Smith (2008) and Doe (2015) suggesting a positive association between air pollution levels and adverse health outcomes, with potential ramifications for public welfare and economic productivity. The deleterious effects of air pollution on human health have been extensively documented, prompting regulatory efforts and public health interventions to mitigate its impact. It is indeed a breath of fresh air to see such comprehensive studies on the topic.

In terms of labor market dynamics, Jones (2012) highlights the influence of environmental factors on employment trends, underscoring the intricate interplay between ecological conditions and economic activities. Despite the serious implications of these findings, it is refreshing to learn about the existing research on this somewhat unconventional relationship.

Expanding beyond these environmental and economic perspectives, "The Air-Pollution-Blender Paradox" by Ellis and Chambers (2017) offers a comprehensive analysis of the surprising correlation between air quality and consumer demand for blenders, providing a thought-provoking exploration of this rather unexpected phenomenon. The book provides a unique blend of environmental science and consumer behavior, shedding light on the interplay between seemingly unrelated domains.

Forging further into the literary abyss, fictional works such as "The Blended Chronicles" by Cinnamon Swirl and "Air Pollution Adventures" by Misty Mountain delve into fantastical worlds where blenders and air pollution take center stage, offering imaginative and whimsical narratives that, albeit unrelated to empirical research, serve as amusing departures from the scholarly realm.

In the realm of popular culture, TV shows such as "Air Quality and the City" and "Blending Beyond Borders" provide anecdotal insights and perhaps unintentional inspiration for our seemingly outlandish research endeavor, proving that reality can be stranger than fiction, and that truth is often more bizarre than the creative mind could imagine.

Indeed, as we navigate through the extensive literature on air pollution, labor markets, and consumer behavior, it becomes apparent that this peculiar confluence of variables is not only a subject of scholarly inquiry but also a fount of unexpected humor and amusement. As the saying goes, "Why did the blender go to therapy? It was having a meltdown!"

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Bozeman, Montana and The number of blender tenders in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Bureau of Larbor Statistics . You used data from 2003 to 2019

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.

With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.

In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!"

[[INTRODUCTION]]
The relationship between environmental factors and labor market trends is often an unexplored territory, akin to traversing through a dense, smog-filled forest with nothing but a blender in hand. However, in the spirit of blending seemingly unrelated ideas, this study delves into the rather unconventional link between air pollution levels in Bozeman, Montana, and the workforce of blender tenders in the state.
Air pollution, a noxious blend of gases and particles, has long been a cause for concern due to its adverse effects on human health and the environment. Yet, who would have thought that amidst this chemical cocktail of pollutants, there lies a hitherto uncharted correlation with the number of individuals tending to the humble blender, the unsung hero of many a kitchen concoction?
Uncovering such unexpected connections between seemingly unrelated variables can be likened to accidentally mixing vinegar with milk – surprising, puzzling, and often leading to unexpected outcomes. Nevertheless, it is within these unexpected outcomes that the potential for groundbreaking discoveries often lies, much like finding a hidden gem in a box of kitchen gadgets.
Integrating data from the Environmental Protection Agency and the Bureau of Labor Statistics, our study aims to unravel the tangled blend of factors influencing the demand for blender tenders in Montana. The analysis uncovers a strong correlation between air pollution levels in Bozeman and the number of blender tenders in the state, akin to finding the perfect blend of ingredients for an elusive recipe.
The unexpected nature of the findings serves as a stark reminder of the complexity of real-world phenomena, akin to discovering a hidden blender feature after years of use – it may be surprising, but it sheds new light on an everyday appliance. As we navigate through the web of air pollution and labor market dynamics, it becomes evident that this seemingly inconspicuous correlation has broader implications for understanding regional economic dynamics amidst environmental challenges.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
Our research team scavenged the depths of the internet, akin to a determined adventurer searching for rare treasures, to collect data on air pollution levels and the number of blender tenders in Montana. The main sources of data included the Environmental Protection Agency (EPA) for air pollution data and the Bureau of Labor Statistics for employment figures. These data spanned from the years 2003 to 2019, providing a comprehensive overview of the dynamics between air quality and blender tender workforce.

Air Pollution Measurement:
The air pollution levels in Bozeman, Montana, were obtained from various monitoring stations within the city. These stations were strategically situated to capture the intricate dance of air pollutants as they swirled and mingled in the atmosphere, not unlike a well-coordinated blender blending its contents to perfection. The data included measurements of particulate matter, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide, representing the diverse ensemble of pollutants present in the atmospheric symphony.

Blender Tender Enumeration:
The number of individuals employed as blender tenders in Montana was extracted from a comprehensive database provided by the Bureau of Labor Statistics. This rather niche category of employment, often overlooked in labor market analyses, presented a unique challenge akin to trying to find the lone blender in a cluttered kitchen cabinet. Nevertheless, our team meticulously sorted through the employment data to identify and quantify the workforce dedicated to tending to blenders of all shapes and sizes across the state.

Data Preprocessing and Analysis:
The obtained data on air pollution levels and blender tender employment underwent rigorous preprocessing to ensure a harmonious blend suitable for analysis. Missing values were imputed, outliers were carefully examined for any interesting deviations, and the data were smoothened and refined like a meticulous chef preparing a velvety soup in a well-worn blender. Following preprocessing, the data were subjected to various statistical analyses, including correlation analysis and regression modeling, to unravel the intricate relationship between air pollution and blender tender numbers.

Just like a well-blended smoothie, every step of the methodology was carefully undertaken to ensure a harmonious and robust analysis of the unexpected correlation between air pollution in Bozeman and the number of individuals tending to blenders in Montana.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Bozeman, Montana and The number of blender tenders in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Bureau of Larbor Statistics .

For the time period 2003 to 2019, you found a correlation 0.8308962, r-squared of 0.6903886, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.

With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.

In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!"

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between environmental factors and labor market trends is often an unexplored territory, akin to traversing through a dense, smog-filled forest with nothing but a blender in hand. However, in the spirit of blending seemingly unrelated ideas, this study delves into the rather unconventional link between air pollution levels in Bozeman, Montana, and the workforce of blender tenders in the state.
Air pollution, a noxious blend of gases and particles, has long been a cause for concern due to its adverse effects on human health and the environment. Yet, who would have thought that amidst this chemical cocktail of pollutants, there lies a hitherto uncharted correlation with the number of individuals tending to the humble blender, the unsung hero of many a kitchen concoction?
Uncovering such unexpected connections between seemingly unrelated variables can be likened to accidentally mixing vinegar with milk – surprising, puzzling, and often leading to unexpected outcomes. Nevertheless, it is within these unexpected outcomes that the potential for groundbreaking discoveries often lies, much like finding a hidden gem in a box of kitchen gadgets.
Integrating data from the Environmental Protection Agency and the Bureau of Labor Statistics, our study aims to unravel the tangled blend of factors influencing the demand for blender tenders in Montana. The analysis uncovers a strong correlation between air pollution levels in Bozeman and the number of blender tenders in the state, akin to finding the perfect blend of ingredients for an elusive recipe.
The unexpected nature of the findings serves as a stark reminder of the complexity of real-world phenomena, akin to discovering a hidden blender feature after years of use – it may be surprising, but it sheds new light on an everyday appliance. As we navigate through the web of air pollution and labor market dynamics, it becomes evident that this seemingly inconspicuous correlation has broader implications for understanding regional economic dynamics amidst environmental challenges.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state revealed a strong correlation coefficient of 0.8308962, signifying a robust association between these seemingly unrelated variables. This substantial correlation coefficient indicates a high degree of linear relationship between the two factors, much like the seamless blending of ingredients in a well-crafted smoothie.

Furthermore, the r-squared value of 0.6903886 suggests that approximately 69.04% of the variability in the number of blender tenders can be explained by the variation in air pollution levels. This significant explanatory power highlights the compelling nature of the relationship, reminiscent of a perfectly executed blend that leaves no room for chunks or lumps.

The p-value of less than 0.01 demonstrates the statistical significance of the observed correlation, indicating that the likelihood of such a strong relationship occurring by chance is exceedingly low. This statistical significance adds weight to the findings, much like an extra scoop of protein powder amplifying the nutritional value of a smoothie.

Interestingly, the scatterplot (Fig. 1) depicting the relationship concisely illustrates the positive linear trend between air pollution levels in Bozeman and the number of blender tenders in Montana. As the air quality declines, there is a discernible uptick in the demand for blender tenders, resembling the consistent whirring sound of a blender as it concocts a delectable mixture.

In summary, the results of this study not only emphasize the surprising correlation between air pollution and the labor market for blender tenders but also underscore the importance of considering unanticipated associations in economic and environmental research. As the saying goes, "When life gives you air pollution, make a smoothie and blend your worries away!"

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Bozeman, Montana and The number of blender tenders in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.

With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.

In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!"

[[LITERATURE REVIEW]]
The authors find Smith (2008) and Doe (2015) suggesting a positive association between air pollution levels and adverse health outcomes, with potential ramifications for public welfare and economic productivity. The deleterious effects of air pollution on human health have been extensively documented, prompting regulatory efforts and public health interventions to mitigate its impact. It is indeed a breath of fresh air to see such comprehensive studies on the topic.
In terms of labor market dynamics, Jones (2012) highlights the influence of environmental factors on employment trends, underscoring the intricate interplay between ecological conditions and economic activities. Despite the serious implications of these findings, it is refreshing to learn about the existing research on this somewhat unconventional relationship.
Expanding beyond these environmental and economic perspectives, "The Air-Pollution-Blender Paradox" by Ellis and Chambers (2017) offers a comprehensive analysis of the surprising correlation between air quality and consumer demand for blenders, providing a thought-provoking exploration of this rather unexpected phenomenon. The book provides a unique blend of environmental science and consumer behavior, shedding light on the interplay between seemingly unrelated domains.
Forging further into the literary abyss, fictional works such as "The Blended Chronicles" by Cinnamon Swirl and "Air Pollution Adventures" by Misty Mountain delve into fantastical worlds where blenders and air pollution take center stage, offering imaginative and whimsical narratives that, albeit unrelated to empirical research, serve as amusing departures from the scholarly realm.
In the realm of popular culture, TV shows such as "Air Quality and the City" and "Blending Beyond Borders" provide anecdotal insights and perhaps unintentional inspiration for our seemingly outlandish research endeavor, proving that reality can be stranger than fiction, and that truth is often more bizarre than the creative mind could imagine.
Indeed, as we navigate through the extensive literature on air pollution, labor markets, and consumer behavior, it becomes apparent that this peculiar confluence of variables is not only a subject of scholarly inquiry but also a fount of unexpected humor and amusement. As the saying goes, "Why did the blender go to therapy? It was having a meltdown!"

[[RESULTS]]
The analysis of the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state revealed a strong correlation coefficient of 0.8308962, signifying a robust association between these seemingly unrelated variables. This substantial correlation coefficient indicates a high degree of linear relationship between the two factors, much like the seamless blending of ingredients in a well-crafted smoothie.
Furthermore, the r-squared value of 0.6903886 suggests that approximately 69.04% of the variability in the number of blender tenders can be explained by the variation in air pollution levels. This significant explanatory power highlights the compelling nature of the relationship, reminiscent of a perfectly executed blend that leaves no room for chunks or lumps.
The p-value of less than 0.01 demonstrates the statistical significance of the observed correlation, indicating that the likelihood of such a strong relationship occurring by chance is exceedingly low. This statistical significance adds weight to the findings, much like an extra scoop of protein powder amplifying the nutritional value of a smoothie.
Interestingly, the scatterplot (Fig. 1) depicting the relationship concisely illustrates the positive linear trend between air pollution levels in Bozeman and the number of blender tenders in Montana. As the air quality declines, there is a discernible uptick in the demand for blender tenders, resembling the consistent whirring sound of a blender as it concocts a delectable mixture.
In summary, the results of this study not only emphasize the surprising correlation between air pollution and the labor market for blender tenders but also underscore the importance of considering unanticipated associations in economic and environmental research. As the saying goes, "When life gives you air pollution, make a smoothie and blend your worries away!"

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The substantial correlation coefficient and statistical significance of the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state supported earlier research that highlighted the unexpected connections between seemingly disparate variables. This aligns with the findings of Smith (2008) and Doe (2015), which emphasized the profound impact of air pollution on various aspects of society. It seems that amidst the dark cloud of air pollution, there is indeed a silver lining in the form of increased demand for blender tenders, akin to finding a refreshing smoothie on a scorching summer day.

The robust association between air pollution and the labor market for blender tenders also resonates with the work of Jones (2012), who delved into the complex interplay between environmental conditions and economic activities. The findings of our study further shed light on this interrelationship, indicating that as the air quality deteriorates, the demand for individuals adept at tending blenders surges, not unlike the consistent churning of a smoothie in the blender.

Moreover, our results echo the sentiments expressed by Ellis and Chambers (2017), who provocatively proposed the existence of the "Air-Pollution-Blender Paradox." This paradox seems less paradoxical now, as our empirical evidence indicates a tangible link between declining air quality and the burgeoning need for blender tenders. It appears that this seemingly incongruous relationship is not only a subject of scholarly interest but also a tangible phenomenon with economic implications, much like the unexpected joy derived from finding an inexplicably amusing joke in a dense academic paper.

The explanatory power of approximately 69.04% conveyed by the r-squared value underscores the strength of the association, akin to the desirable smooth texture of a well-blended concoction. This robust explanatory power, combined with the statistical significance of the observed correlation, lends weight to the argument that air pollution levels play a substantial role in shaping the labor market for blender tenders, much like a perfectly ripe banana contributes to a delectable smoothie.

In conclusion, our study has not only illuminated an intriguing link between air pollution and blender tender employment but has also underscored the value of examining unexpected associations in environmental and economic research. This unexpected connection, much like an out-of-place dad joke in a serious academic paper, serves as a reminder that reality is often more whimsical than anticipated and that seemingly unrelated variables may indeed converge in surprising ways.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Bozeman, Montana and The number of blender tenders in Montana. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana"

[[ABSTRACT]]
This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.

With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.

In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!"

[[INTRDUCTION]]
The relationship between environmental factors and labor market trends is often an unexplored territory, akin to traversing through a dense, smog-filled forest with nothing but a blender in hand. However, in the spirit of blending seemingly unrelated ideas, this study delves into the rather unconventional link between air pollution levels in Bozeman, Montana, and the workforce of blender tenders in the state.
Air pollution, a noxious blend of gases and particles, has long been a cause for concern due to its adverse effects on human health and the environment. Yet, who would have thought that amidst this chemical cocktail of pollutants, there lies a hitherto uncharted correlation with the number of individuals tending to the humble blender, the unsung hero of many a kitchen concoction?
Uncovering such unexpected connections between seemingly unrelated variables can be likened to accidentally mixing vinegar with milk – surprising, puzzling, and often leading to unexpected outcomes. Nevertheless, it is within these unexpected outcomes that the potential for groundbreaking discoveries often lies, much like finding a hidden gem in a box of kitchen gadgets.
Integrating data from the Environmental Protection Agency and the Bureau of Labor Statistics, our study aims to unravel the tangled blend of factors influencing the demand for blender tenders in Montana. The analysis uncovers a strong correlation between air pollution levels in Bozeman and the number of blender tenders in the state, akin to finding the perfect blend of ingredients for an elusive recipe.
The unexpected nature of the findings serves as a stark reminder of the complexity of real-world phenomena, akin to discovering a hidden blender feature after years of use – it may be surprising, but it sheds new light on an everyday appliance. As we navigate through the web of air pollution and labor market dynamics, it becomes evident that this seemingly inconspicuous correlation has broader implications for understanding regional economic dynamics amidst environmental challenges.

[[RESULTS]]
The analysis of the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state revealed a strong correlation coefficient of 0.8308962, signifying a robust association between these seemingly unrelated variables. This substantial correlation coefficient indicates a high degree of linear relationship between the two factors, much like the seamless blending of ingredients in a well-crafted smoothie.
Furthermore, the r-squared value of 0.6903886 suggests that approximately 69.04% of the variability in the number of blender tenders can be explained by the variation in air pollution levels. This significant explanatory power highlights the compelling nature of the relationship, reminiscent of a perfectly executed blend that leaves no room for chunks or lumps.
The p-value of less than 0.01 demonstrates the statistical significance of the observed correlation, indicating that the likelihood of such a strong relationship occurring by chance is exceedingly low. This statistical significance adds weight to the findings, much like an extra scoop of protein powder amplifying the nutritional value of a smoothie.
Interestingly, the scatterplot (Fig. 1) depicting the relationship concisely illustrates the positive linear trend between air pollution levels in Bozeman and the number of blender tenders in Montana. As the air quality declines, there is a discernible uptick in the demand for blender tenders, resembling the consistent whirring sound of a blender as it concocts a delectable mixture.
In summary, the results of this study not only emphasize the surprising correlation between air pollution and the labor market for blender tenders but also underscore the importance of considering unanticipated associations in economic and environmental research. As the saying goes, "When life gives you air pollution, make a smoothie and blend your worries away!"

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the results of this study offer compelling evidence of a strong correlation between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. This unexpected association, akin to finding a blender at a car dealership, has significant implications for understanding the interplay between environmental factors and labor market dynamics.

The substantial correlation coefficient and statistical significance of the observed relationship highlight the need to consider unorthodox connections in economic and environmental research, much like realizing that a blender can also be used to mix cement – it may not be the intended purpose, but it gets the job done.

Furthermore, the high explanatory power of the relationship underscores the potential influence of air pollution on the demand for blender tenders, akin to realizing that a good smoothie can silence the loudest blender jokes.

Given these findings, it is evident that further investigation into the underlying mechanisms driving this correlation, and its broader implications for employment trends and environmental policy, are warranted. Nevertheless, it is clear that the unexpected connection between air pollution and the labor market for blender tenders warrants additional attention, much like how a good smoothie recipe demands just the right amount of attention to detail.

In essence, this study serves as a reminder that seemingly unrelated variables may hold surprising connections, much like discovering that a blender's true calling is not just to make smoothies, but also to provide insight into regional economic dynamics. As such, it is reasonable to assert that no further research in this area is needed. After all, when it comes to blending air pollution and blender tenders, we've already achieved a perfect mix!

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Ecological Appliance Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana. Respond only with the name of a fictional organization.

ChatGPT:

Society for the Advancement of Rustic Environmental Research and Studies (SARERS)

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana with an abstract of This study investigates the relationship between air pollution levels in Bozeman, Montana, and the number of blender tenders in the state. Utilizing data from the Environmental Protection Agency and the Bureau of Labor Statistics for the years 2003 to 2019, a strong correlation coefficient of 0.8308962 and significant p-value of less than 0.01 were observed. Despite the seemingly unrelated nature of the two variables, the findings are quite striking.
With air pollution as a detrimental factor to public health, it is crucial to understand its potential impact on various facets of society, including employment. Surprisingly, our research uncovered a noteworthy association between higher air pollution levels in Bozeman and an increase in the number of blender tenders throughout Montana. It seems that as the air quality decreases, the demand for blending technologies sharply rises, indicating a novel avenue for economic growth amidst environmental concerns.
In conclusion, our study provides valuable insights into the unexpected connection between environmental factors and labor market dynamics, shedding light on the importance of examining seemingly disparate variables. As the old saying goes, "Where there's air pollution, there's a blender in need of tendering!

ChatGPT:

air pollution, blender tenders, Bozeman Montana, correlation, Environmental Protection Agency, Bureau of Labor Statistics, employment, public health, economic growth, labor market dynamics

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Air pollution in Bozeman, Montana
Detailed data title: Percentage of days with moderate or worse air quality in Bozeman, MT
Source: Environmental Protection Agency
See what else correlates with Air pollution in Bozeman, Montana

The number of blender tenders in Montana
Detailed data title: BLS estimate of mixing and blending machine setters, operators, and tenders in Montana
Source: Bureau of Larbor Statistics
See what else correlates with The number of blender tenders in Montana

Correlation r = 0.8308962 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.6903886 (Coefficient of determination)
This means 69% of the change in the one variable (i.e., The number of blender tenders in Montana) is predictable based on the change in the other (i.e., Air pollution in Bozeman, Montana) over the 17 years from 2003 through 2019.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.61E-5.^Show 0.0000360899164101591960000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.83 in 0.00361% of random cases. Said differently, if you correlated 27,709 random variables^Note You don't actually need 27 thousand variables to find a correlation like this one. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 16 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.58, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019
Air pollution in Bozeman, Montana (Bad air quality days)	0.047486	0.0601093	0.0575342	0.131507	0.169863	0.125683	0.213699	0.230137	0.232877	0.166667	0.0849315	0.109589	0.126027	0.13388	0.210959	0.115068	0.0767123
The number of blender tenders in Montana (Laborers)	100	120	130	170	220	280	360	320	290	250	220	160	270	250	240	210	170

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.047486,0.0601093,0.0575342,0.131507,0.169863,0.125683,0.213699,0.230137,0.232877,0.166667,0.0849315,0.109589,0.126027,0.13388,0.210959,0.115068,0.0767123,])
array_2 = np.array([100,120,130,170,220,280,360,320,290,250,220,160,270,250,240,210,170,])
array_1_name = "Air pollution in Bozeman, Montana"
array_2_name = "The number of blender tenders in Montana"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
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Line chart for only Air pollution in Bozeman, Montana
Line chart for only The number of blender tenders in Montana
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The spurious research paper: Blendin' in Bozeman: Exploring the Correlation Between Air Pollution and Blender Tender Numbers in Montana

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Correlation ID: 5486 · Black Variable ID: 22285 · Red Variable ID: 10823


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